https://github.com/wenbihan/vidosat_icip2015
ViDOSAT video denoising codes, Matlab implementation. ICIP2015 paper
https://github.com/wenbihan/vidosat_icip2015
icip low-latency online-learning transform-learning video video-denoising
Last synced: 6 months ago
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ViDOSAT video denoising codes, Matlab implementation. ICIP2015 paper
- Host: GitHub
- URL: https://github.com/wenbihan/vidosat_icip2015
- Owner: wenbihan
- Created: 2017-10-14T20:17:53.000Z (about 8 years ago)
- Default Branch: master
- Last Pushed: 2019-04-03T10:21:46.000Z (over 6 years ago)
- Last Synced: 2025-04-03T06:23:32.845Z (7 months ago)
- Topics: icip, low-latency, online-learning, transform-learning, video, video-denoising
- Language: MATLAB
- Homepage: http://transformlearning.csl.illinois.edu/
- Size: 39.8 MB
- Stars: 11
- Watchers: 2
- Forks: 2
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# VIDOSAT video denoising
=============
ViDOSAT video denoising accompanies the following publication:
"Video denoising by online 3D sparsifying transform learning", IEEE International Conference on Image Processing (ICIP), 2015. [ICIP 2015](http://ieeexplore.ieee.org/abstract/document/7350771/), [PDF available](http://transformlearning.csl.illinois.edu/assets/Bihan/ConferencePapers/BihanSaiICIP2015VIDOLSAT.pdf)
Description:
-----
VIDOSAT is a video denoising framework based on online 3D spatio-temporal sparsifying transform learning. The proposed scheme has low computational and memory costs, and can potentially handle streaming video. Our numerical experiments show promising performance for the proposed video denoising method compared to popular prior or state-of-the-art methods.
The VIDOSAT package includes (1) a collection of the VIDOSAT Matlab functions, and (2) example demo data used in the VIDOSAT paper for video denoising.
You can download our other software packages at: [My Homepage](http://web.engr.illinois.edu/~bwen3/) and [Transform Learning Site](http://transformlearning.csl.illinois.edu/).
Paper
In case of use, please cite our publications:
B. Wen, S. Ravishankar, and Y. Bresler. “Video denoising by online 3D sparsifying transform learning." IEEE International Conference on Image Processing (ICIP), pp. 118 - 122, 2015.
```
@inproceedings{wen2015vidosat,
title={Video denoising by online 3D sparsifying transform learning},
author={Wen, Bihan and Ravishankar, Saiprasad and Bresler, Yoram},
booktitle={IEEE International Conference on Image Processing (ICIP)},
pages={118--122},
year={2015},
organization={IEEE}
}
```
Use
---
All codes are subject to copyright and may only be used for non-commercial research. In case of use, please cite our publication.
Contact Bihan Wen (bihan.wen.uiuc@gmail.com) for any questions.
Acknowledgement
---
The development of this software was supported in part by the National Science Foundation (NSF) under grants CCF 06-35234 and CCF 10-18660.